ArticleContraception2011
Quantitative perceptual differences among over-the-counter vaginal products using a standardized methodology: implications for microbicide development.
Article in Contraception, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Trial
- Antimicrobial Activity of a Vaginal Gel Formulation: Considerations Related to Vaginal Infection and Dysbiosis.Pathogens (Basel, Switzerland) · 2021Article
- A Comparison of Two Sensory Panels Trained with Different Feedback Calibration Range Specifications via Sensory Description of Five Beers.Foods (Basel, Switzerland) · 2019Article
- On-demand microbicide products: design matters.Drug delivery and translational research · 2017Review
- Designing and developing suppository formulations for anti-HIV drug delivery.Therapeutic delivery · 2017Review
- Drivers of Vaginal Drug Delivery System Acceptability from Internet-Based Conjoint Analysis.PloS one · 2016Article
- Article
- Designing preclinical perceptibility measures to evaluate topical vaginal gel formulations: relating user sensory perceptions and experiences to formulation properties.AIDS research and human retroviruses · 2014Article
- Shape of vaginal suppositories affects willingness-to-try and preference.Antiviral research · 2013Article
- Acceptability in microbicide and PrEP trials: current status and a reconceptualization.Current opinion in HIV and AIDS · 2012Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundIncreasing prevalence of HIV infection among women worldwide has motivated the development of female-initiated prevention methods, including gel-based microbicides. User acceptability is vital for microbicide success; however, varying cultural vaginal practices indicate multiple formulations must be developed to appeal to different populations. Perceptual attributes of microbicides have been identified as primary drivers of acceptability; however, previous studies do not allow for direct comparison of these qualities between multiple formulations. STUDY
designSix vaginal products were analyzed ex vivo using descriptive analysis. Perceptual attributes of samples were identified by trained participants (n=10) and rated quantitatively using scales based on a panel-developed lexicon. Data were analyzed using two-way ANOVAs for each attribute; product differences were assessed via Tukey's honestly significant difference test.
resultsSignificant differences were found between products for multiple attributes. Patterns were also seen for attributes across intended product usage (i.e., contraceptive, moisturizer or lubricant). For example, Options© Gynol II® (Caldwell Consumer Health, LLC) was significantly stickier and grainier than other products.
conclusionsDescriptive analysis, a quantitative approach that is based on consensus lexicon usage among participants, successfully quantified perceptual differences among vaginal products. Since perceptual attributes of products can be directly compared quantitatively, this study represents a novel approach that could be used to inform rational design of microbicides.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.